In this paper, we consider the fundamental problem of channel estimation in multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems operating over random channels. Using the Bayesian framework, linear minimum mean square error (LMMSE) and expectation-maximization (EM) based maximum a posteriori (MAP) channel estimation algorithms are developed, that provide the destination with full knowledge of all channel parameters involved in the transmission. The performance of the proposed algorithms is evaluated in terms of the mean square error (MSE) as a function of the signal-to-noise ratio (SNR) during the training interval. Our simulation results show that the incorporation of prior knowledge into the channel estimation algorithm offers improved performance, especially in the low SNR regime.

We propose and analyze eigenbeam transmission over line-of-sight (LOS) multiple-input multiple-output (MIMO) channels with linear reception. In particular, we consider fixed point-to-point microwave links for which the singular value decomposition of the LOS MIMO channel matrix is analytically derived. We demonstrate that the Tx eigenbeams can be defined without channel state information at the transmitter and that the beams admit an insightful physical interpretation. We also evaluate the performance of a lattice-reduction aided linear receiver through numerical simulations.

We propose a novel, coordinated user scheduling (CUS) algorithm for inter-cell interference (ICI) mitigation in the downlink of a multi-cell multi-user MIMO system. In the proposed algorithm, ICI mitigation is performed through the exchange of necessary channel state information (CSI) among the base stations, and the revision of the scheduling decisions and beamformer designs at each base station. Furthermore, ICI mitigation is performed only for the cell-edge users so that the amount of inter-base station signaling overhead is minimized. Our simulation results demonstrate that the proposed coordination scheduling algorithm significantly improves the cell-edge users' throughput compared to conventional systems with only a negligible amount of CSI sharing among the base stations and a relatively small throughput loss for the cell-interior users.

We study the downlink of a multicell MIMO system where clusters of multi-antenna base stations jointly serve multiple single-antenna users, commonly referred to as a network MIMO system. Most of the previous studies on network MIMO have only considered the azimuth pattern of the antenna, while ignoring the elevation pattern. In this paper, we consider both the azimuth and the elevation patterns and investigate the impact of the elevation angle tuning parameter, denoted as the antenna tilt, on the performance of such systems. Using system simulations, it is shown that the promised performance gains of network MIMO systems over conventional non-coordinated systems, crucially depend on the choice of the right tilt setting including the tilt type, i.e., mechanical or electrical, and the tilt angle. In particular, for tilt angles smaller than the optimum, network MIMO with intra-site coordination performs almost as well as the conventional system; while for tilt angles larger than the optimum, the performance of network MIMO with intra-site is similar to that of network MIMO with inter-site coordination.